Scalability improvement of a data processing framework

The iTrack is a backend system developed by a company working with GPS tracking. The backend has many users and sub-systems connected to it at the same time. A data processing framework is also the part of iTrack, which processes data that is received from tracked vehicles (e.g. GPS coordinates). The processing can happen in real time, or later. My task was to improve the scalability of this framework, including examining the possibilities, giving suggestions for the improvement, then choosing the most rewarding solution and implementing it.

First of all, I want to describe the related part of the iTrack backend, which gave the base of my tasks. Then I detail why the changes were so necessary, what were the options, what problems occurred during the implementation, and what kind of influence they have on the planned changes.

I will describe what preparations and additional knowledge were needed to make the changes, followed by the important aspects of scalability. I will mention the progress of the changes, testing results, and practical benefits.

Lastly I will summarize the reached goals, the resulting improvements, and the next possible actions to take for further scaling.